An automotive sensor integration module including a plurality of sensors which differ in at least one of a sensing period or an output data format, and a signal processor, which simultaneously outputs, as sensing data, pieces of detection data respectively output from the plurality of sensors on the basis of the sensing period of any one of the plurality of sensors, calculates a reliability value of each of the pieces of detection data on the basis of the pieces of detection data and external environment data, and outputs the reliability value as reliability data.
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2. The automotive sensor integration module of claim 1, wherein the signal processor receives and stores the pieces of detection data, and simultaneously outputs the stored pieces of detection data on the basis of the sensing period of any one of the plurality of sensors.
This invention relates to an automotive sensor integration module designed to improve data synchronization and processing in vehicles equipped with multiple sensors. The module addresses the challenge of managing detection data from various sensors, which may operate at different sensing periods, ensuring timely and coordinated output for vehicle control systems. The module includes a signal processor that receives and stores detection data from multiple sensors. The signal processor is configured to output the stored data simultaneously based on the sensing period of any one of the sensors. This ensures that data from all sensors is aligned and available at the same time, regardless of their individual sampling rates. The module also includes a communication interface for transmitting the processed data to other vehicle systems, such as an electronic control unit (ECU), for further analysis and decision-making. By synchronizing the output of sensor data, the module enhances the accuracy and reliability of vehicle operations, such as adaptive cruise control, collision avoidance, and autonomous driving functions. The invention improves data consistency, reduces processing delays, and ensures that all sensor inputs are available when needed, addressing a critical need in modern automotive systems.
3. The automotive sensor integration module of claim 1, wherein the signal processor increases or decreases the reliability values of the pieces of detection data according to the number of occurrences of data which enables at least one of color discrimination or distance determination from the pieces of detection data.
This invention relates to an automotive sensor integration module designed to improve the reliability of detection data from multiple sensors in a vehicle. The module processes sensor data to enhance the accuracy of color discrimination and distance determination, which are critical for autonomous driving and advanced driver-assistance systems (ADAS). The system addresses the challenge of integrating data from diverse sensors, such as cameras, LiDAR, and radar, which may produce inconsistent or unreliable outputs under varying conditions. The module includes a signal processor that adjusts the reliability values of detection data based on the frequency of occurrences where the data enables color discrimination or distance determination. For example, if a sensor frequently provides data that allows accurate color identification, its reliability value is increased, while unreliable or inconsistent data is downweighted. This dynamic adjustment ensures that the most dependable sensor inputs are prioritized in decision-making processes, improving overall system performance. The module also integrates data from multiple sensors, normalizes the data, and applies fusion algorithms to generate a unified output. This output is used for tasks such as object detection, tracking, and classification, which are essential for safe and efficient vehicle operation. The invention enhances the robustness of sensor-based systems by dynamically adapting to sensor performance variations, ensuring reliable operation in real-world driving scenarios.
4. The automotive sensor integration module of claim 3, wherein the signal processor increases the reliability values of the pieces of detection data as the number of occurrences of data which enables at least one of color discrimination or distance determination from the pieces of detection data increases.
This invention relates to an automotive sensor integration module designed to enhance the reliability of detection data from multiple sensors in a vehicle. The module processes data from various sensors, such as cameras, radar, and lidar, to improve color discrimination and distance determination. The system assigns reliability values to the detection data, which are dynamically adjusted based on the frequency of occurrences where the data enables accurate color discrimination or distance measurement. As the number of such occurrences increases, the reliability values of the corresponding data are incrementally raised, ensuring more accurate and trustworthy sensor outputs for vehicle systems like autonomous driving, collision avoidance, and object tracking. The module integrates data from different sensors, normalizes it, and applies reliability-based filtering to improve overall detection performance. This approach mitigates errors caused by sensor noise, environmental interference, or partial sensor failures, leading to more robust and dependable sensor fusion in automotive applications. The system dynamically adapts to changing conditions, ensuring consistent reliability improvements over time.
5. The automotive sensor integration module of claim 1, wherein the signal processor increases or decreases the reliability values of the pieces of detection data according to whether a data value difference occurs between current data and previous data of the pieces of detection data.
6. The automotive sensor integration module of claim 5, wherein the signal processor increases the reliability values of the pieces of detection data when the data value difference occurs between the current data and the previous data of the pieces of detection data.
7. The automotive sensor integration module of claim 1, wherein the signal processor increases or decreases the reliability values of the pieces of detection data according to whether it rains or snows or a road is paved on the basis of the external environment data.
8. The automotive sensor integration module of claim 7, wherein the signal processor decreases the reliability values of the pieces of detection data to a greater degree when it rains or snows than when it does not rain or snow.
This invention relates to an automotive sensor integration module designed to improve the accuracy of vehicle sensor data in adverse weather conditions. The module processes detection data from multiple sensors, such as cameras, radar, and LiDAR, to enhance situational awareness for autonomous driving or advanced driver-assistance systems (ADAS). A key challenge addressed is the degradation of sensor performance in rain or snow, which can lead to unreliable detection data. The module includes a signal processor that adjusts the reliability values of the detection data based on environmental conditions. When rain or snow is detected, the processor reduces the reliability values of the sensor data more significantly than in clear weather. This adjustment helps mitigate errors caused by precipitation, ensuring that the system relies less on potentially compromised data. The module may also incorporate a weather detection system, such as a rain sensor or external weather data feed, to determine the presence of rain or snow. By dynamically adjusting reliability values, the module improves the overall accuracy of sensor fusion, reducing false positives and enhancing decision-making for autonomous driving functions. This approach ensures safer and more reliable operation in varying weather conditions.
9. The automotive sensor integration module of claim 8, wherein the signal processor decreases the reliability values of the pieces of detection data to a greater degree when a vehicle travels on an unpaved road than when the vehicle travels on a paved road.
13. The automotive sensor integration module of claim 11, wherein the output synchronization unit receives and stores the pieces of detection data, and simultaneously outputs the stored pieces of detection data on the basis of the sensing period of any one of the plurality of sensors.
14. The automotive sensor integration module of claim 11, wherein the plurality of sensors comprise at least one of an optical camera, an infrared camera, a radar, or a lidar.
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December 24, 2019
November 8, 2022
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